一种增强成像大气切伦科夫望远镜伽马-质子鉴别能力的方法
A method for enhanced gamma-proton discrimination with imaging atmospheric Cherenkov telescopes
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中文总结 AI 辅助
针对成像大气切伦科夫望远镜伽马-质子鉴别能力不足的问题，提出基于切伦科夫光子发射位置横向分布的新观测量，并结合似然比方法，在1 TeV附近将鉴别性能提升约一个数量级。
中文摘要 AI 辅助
目的：甚高能伽马射线天文学是研究宇宙中极端天体物理过程的重要窗口，而如何有效区分伽马光子与背景信号（主要是质子）是实现甚高能伽马射线探测的关键技术挑战。星载量能器记录次级粒子的空间分布，在1 TeV附近实现了10000-100000的背景抑制能力。地基成像切伦科夫望远镜测量切伦科夫光子的角分布，然而在该能量范围内仅能达到约10的抑制因子，存在很大的优化空间。方法：我们使用CORSIKA和sim_telarray模拟H.E.S.S.探测器响应。从切伦科夫簇射图像中重建光子发射位置。受星载量能器分析技术的启发，我们提出了基于切伦科夫光子发射位置横向分布的新观测量，以区分伽马射线信号与质子背景。我们采用似然比方法将多个望远镜的单望远镜变量进行组合，并将其性能与基于Hillas变量的传统分析进行比较。结果：结果表明，基于切伦科夫光子发射位置横向分布构建的观测量对切伦科夫图像尺寸的敏感性较低，并且在单望远镜伽马-质子鉴别方面优于Hillas宽度参数。此外，结合宽度的似然比方法比传统的平均缩减标度宽度性能显著更好：在1 TeV附近改进幅度约达一个数量级，且对于10 TeV以上的能量，该增强仍保持在50%以上。
英文摘要
Purpose: Very-high-energy gamma-ray astronomy is an important window to study the extreme astrophysical processes in the universe, and how to effectively distinguish between gamma photons and background signals (mainly protons) is a key technical challenge to realize very-high-energy gamma-ray detection. Spaceborne calorimeters record secondary particle spatial distributions, achieving a background rejection power of 10000-100000 near 1 TeV. Ground-based imaging Cherenkov telescopes measure Cherenkov photon angular distributions, yet they only reach a rejection factor of about 10 in this energy range, leaving substantial room for optimization. Methods: We use CORSIKA and sim_telarray to simulate H.E.S.S. detector responses. Photon emission positions are reconstructed from Cherenkov shower images. Inspired by analysis techniques for space-borne calorimeter, we propose new observables derived from the transverse distribution of Cherenkov photon emission positions to separate gamma-ray signals from proton backgrounds. We employ a likelihood-ratio method to combine single-telescope variables across multiple telescopes and compare its performance with conventional Hillas-based analysis. Results: The results show that observables built from the transverse distribution of Cherenkov photon emission positions are less sensitive to Cherenkov image size and outperform the Hillas width parameter for single-telescope gamma-proton discrimination. Furthermore, the likelihood ratio combining width yields substantially better performance than the conventional mean reduced scaled width: the improvement reaches roughly one order of magnitude near 1 TeV, and this enhancement remains above 50% for energies above 10 TeV.
发表机构
- School of Physical Science and Technology, Southwest Jiaotong University（西南交通大学物理科学与技术学院）
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